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Four Two Rants on Mobile Computing

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Title: Four Two Rants on Mobile Computing


1
Four Two Rants on Mobile Computing
  • Jason I. Hong
  • Feb 20 2007
  • Carnegie Mellon University
  • Intel Ultra-Mobile Devices Workshop

2
Two Rants on Mobile Computing
  • Text input is terrible
  • Facing new privacy and security risks
  • Cross-platform issues stifle wide-scale
    deployment
  • Conducting realistic user evaluations difficult

3
Rant 1 Text Input is Terrible
  • Standard phones
  • Multi-tap, 8-20 wpm, world record 29 wpm
  • T9, 20 wpm
  • Special hardware
  • Twiddler, 26-47 wpm (training)
  • Pen
  • QWERTY, 34 wpm
  • IBM SHARK (pen), 60-70 wpm
  • Stuck with 20 wpm for near future

4
Rant 1 Text Input is Terrible
  • Observation dont have to support generic text
    input
  • Support input for tasks that are common when
    mobile
  • inTouch
  • Leverage daily rhythms and real-time context
  • Improve group awareness and messaging
  • GurunGo
  • Use existing desktop web browsing activities
  • Improve information retrieval while on the go

5
inTouch Mobile Group Coordination
  • Goal Better coordination for small mobile groups
  • Contextual awareness
  • Contextual messaging

6
Project InTouch
Its 430pm and Mom is stuck in traffic
inTouch checks her calendar and sees shes
supposed to pick up Cindy from ballet
7
Project InTouch
Moms phone senses that she is in a traffic jam,
and automatically prepares a status message
Mom hits send, and Cindy sees that Mom is
running late. Cindy decides to wait inside.
8
inTouch Mobile Group Coordination
  • Using context to
  • Select a message template
  • Fill in the blanks (like a MadLib)
  • When is contextual messaging useful?
  • Calendar alarms (running late, will be there in
    ltETAgt)
  • Current activity (Im in a meeting, done at
    lttimegt)
  • Daily rhythms (Picked up kid ok at 3PM)
  • Messages received (Where r u? -gt I am at
    ltplacegt)
  • Currently developing a working prototype

9
GurunGo
  • Goal Make it easy to access useful information
    while mobile
  • Observation 1 People still tend to print out
    online maps, despite having mobile device. Why?
  • Found it via desktop, easier to print than to
    copy to mobile
  • Slow or expensive wireless connections
  • Inconvenient form factor on mobile device
  • Observation 2 People dont do the same kind of
    web browsing on mobile phones as on desktops
  • Dont have to support all information finding
    tasks, just ones more likely to be done when
    mobile

10
GurunGo Scenarios
  • Idea Tie mobile more closely with desktop
  • You find an interesting product while browsing
  • Use GurunGo to copy-and-paste to mobile
  • Augments with product reviews
  • Copies to mobile
  • Kept until explicitly deleted
  • As you browse web on desktop
  • GurunGo scans HTML for maps
  • Generates speech-based directions
  • Copies to mobile
  • Directions eventually discarded after given time

11
GurunGo Usage
  • Acquire
  • Let people explicitly copy-and-paste info to
    mobile
  • Let people implicitly copy info via regular web
    browsing
  • GurunGo scans pages seen for potentially useful
    stuff
  • Augment
  • Look for known data types, make mobile data more
    useful
  • Ex. Augment maps with speech-based directions
  • Copy (to mobile in the background)
  • Browse
  • Organize data based on common data types
  • Street addresses, product comparisons, phone s

12
GurunGo Speech-based Directions
13
Nice Features of GurunGo
  • Reduces number of clicks to get to useful
    information
  • Can support specific information finding tasks
    while mobile
  • Currently Directions, products
  • Future Movies, phone s, dates and times, recent
    emails
  • Works even if you dont have wide-area wireless
  • Works disconnected (no network or dont want to
    pay)
  • Only needs personal area network (Bluetooth)

14
Rant 2 New Privacy and Security Risks
  • Mobile devices becoming intimate part of our
    lives
  • Mobile communication
  • Mobile e-commerce
  • Sharing location information with others
  • Unlock doors in home
  • Leads to lots of new risks
  • Mobile spyware (tracks location, already
    starting)
  • Steal and punch thru corporate firewalls
  • Device lost, embarrassment

15
User Controllable Privacy and Security
  • Goal Make it easy for people to manage privacy
    and security policies for pervasive computing
  • Simple UIs for specifying policies
  • Clear notifications and explanations of what
    happened
  • Better visualizations to summarize results
  • Machine learning for learning preferences
  • Start with small evaluations, continue with
    large-scale ones
  • Large multi-disciplinary team and project
  • Six faculty, 1.5 postdocs, six students
  • Supported by NSF, CMU CyLab
  • Roughly 1 year into project

16
Contextual Instant Messaging
  • Facilitate coordination and communication by
    letting people request contextual information via
    IM
  • Interruptibility (via SUBTLE toolkit)
  • Location (via Place Lab WiFi positioning)
  • Active window
  • Developed a custom client and robot on top of AIM
  • Client (Trillian plugin) captures and sends
    context to robot
  • People can query imbuddy411 robot for info
  • howbusyis username
  • Robot also contains privacy rules governing
    disclosure

17
Contextual Instant MessagingPrivacy Mechanisms
  • Web-based specification of privacy preferences
  • Users can create groups andput screennames into
    groups
  • Users can specify what each group can see

18
Contextual Instant MessagingPrivacy Mechanisms
  • Notifications of requests

19
Contextual Instant MessagingPrivacy Mechanisms
  • Social translucency

20
Contextual Instant MessagingPrivacy Mechanisms
  • Audit logs

21
People Finder
  • Location useful for micro-coordination
  • Meeting up
  • Okayness checking
  • Developed phone-based client
  • GSM localization (Intel)
  • Conducted studies to see how people specify
    rules ( how well)
  • See how well machine learning can learn
    preferences

22
Grey Access Control to Resources
  • Distributed smartphone-based access control
    system
  • physical resources like office doors, computers,
    and coke machines
  • electronic ones like computer accounts and
    electronic files
  • currently only physical doors
  • Proofs assembled from credentials
  • No central access control list
  • End-users can create flexible policies

23
Some Early Lessons
  • People dont seem to think about things in terms
    of privacy and security, more of value
    proposition
  • Need large network effects to study some things
  • Right now, only seeing small interesting results
  • Believe we will find interesting results with
    LOTS of people
  • Machine learning seems promising
  • Social psychology issues
  • Projecting a desired persona, plausible
    deniability
  • Cornwell, J., et al. User-Controllable Security
    and Privacy for Pervasive Computing. In the
    Proceedings of The 8th IEEE Workshop on Mobile
    Computing Systems and Applications (HotMobile
    2007).

24
Other Rants (Briefly)
  • Rant 3 Cross-platform issues stifling
    wide-scale deployability
  • Symbian, Nokia, Palm, Windows Mobile, Blackberry
  • All incompatible!
  • J2ME only helps a little
  • Severely limits deployability and usage of apps
  • Rant 4 Conducting realistic user evals
    difficult
  • Hard to do lab studies since (by definition)
    mobile
  • Hard to observe while mobile
  • Majority of people already have phones (contacts,
    phone)

25
Summary
  • Text input is terrible
  • Likely we will be stuck with 20wpm
  • Leverage real-time context to support specific
    mobile information finding tasks rather than
    generic ones
  • Facing new privacy and security risks
  • This may be an Achilles heel for pervasive
    computing
  • Hard, and lots of devices to manage
  • Our work looks at making it easy for people to
    specify, visualize, and manage their privacy and
    security policies

26
Backup Slides
27
Usability Issues
  • 20 of WiFi access points returned
  • People couldnt figure out how to make it work
  • My guess 80 of unsecured WiFi access points
  • When you are mobile, risk of eavesdroppers
  • Computer security too hard to understand, too
    hard to setup

28
Usability Issues
  • Phishing really really works
  • Exact numbers hard to find, but LOTS of people
    fall for them
  • Semantic gap between us and everyday users
  • SSL, certificates, encryption, man-in-the-middle
    attacks
  • But simple phishing is stunningly effective
  • Observation need security models that are
    invisible (managed by others) or extremely easy
    to understand

Civilization advances by extending the number of
operations we can perform without thinking about
them. - Alfred North Whitehead
29
Cultural Issues
  • Browser Cookies
  • Originally meant for maintaining state
  • Now a pervasive means for tracking people online
  • Embedded in every browser, hard to change
  • Observation Security hard issue to wrap brain
    around
  • Hard to assess risk of low-probability event in
    future
  • Adds to cost of development for uncertain benefit
  • Thus, often done as an afterthought (ie too late)

30
Economic Issues
  • Estimated cost of phishing in US is 5 billion
  • Solutions already exist
  • Two-factor authentication
  • Email authentication
  • But
  • Non-computer scams 200 billion
  • Estimated cost of implementation gt 5 billion
  • Observation Many solutions are out there, but
  • Need to align needs of various parties (politics)
  • Need incentives (cost-benefit, law)
  • Observation Scammers getting more sophisticated
  • Market for scammers (setup steal, mules,
    bookkeeping)
  • Build it, and scammers will also come

31
No Secure Mobile Computing Soon
  • Lots of important info on mobile devices
  • Usability issues
  • Cultural issues
  • Economic issues

IEEE Computer, Dec 2005 Minimizing Security
Risks in Ubicomp Systems Invisible Computing
Column
32
GurunGo Product Reviews
33
Rant 2 New Privacy and Security Risks
This was just March 2006
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